mirror of
https://github.com/MLSysBook/TinyTorch.git
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f81ab97100
Separate required vs optional dependencies in health checks: Required (from requirements.txt): - NumPy, Rich, PyYAML, Pytest, Jupytext Optional (nice to have): - JupyterLab, Matplotlib Now health check shows: - Required deps as ✅ OK or ❌ Missing - Optional deps as ✅ Installed or ○ Not installed (dim, not alarming) This prevents students from thinking they have issues when optional tools like JupyterLab aren't installed. 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
106 lines
3.8 KiB
Python
106 lines
3.8 KiB
Python
"""
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Configuration management for TinyTorch CLI.
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"""
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import os
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import sys
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from pathlib import Path
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from typing import Dict, Any, Optional, List, Union
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from dataclasses import dataclass
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@dataclass
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class CLIConfig:
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"""Configuration for TinyTorch CLI."""
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# Project paths
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project_root: Path
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assignments_dir: Path
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tinytorch_dir: Path
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bin_dir: Path
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modules_dir: Path # Alias for assignments_dir
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# Environment settings
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python_min_version: tuple = (3, 8)
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required_packages: list = None # type: ignore
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# CLI settings
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verbose: bool = False
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no_color: bool = False
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def __post_init__(self):
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"""Initialize default values."""
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if self.required_packages is None:
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# Core dependencies from requirements.txt (required section)
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self.required_packages = ['numpy', 'rich', 'yaml', 'pytest', 'jupytext']
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@classmethod
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def from_project_root(cls, project_root: Optional[Path] = None) -> 'CLIConfig':
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"""Create config from project root directory."""
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if project_root is None:
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# Auto-detect project root
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current = Path.cwd()
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while current != current.parent:
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if (current / 'pyproject.toml').exists():
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project_root = current
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break
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current = current.parent
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else:
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project_root = Path.cwd()
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modules_path = project_root / 'src'
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return cls(
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project_root=project_root,
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assignments_dir=project_root / 'assignments',
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modules_dir=modules_path,
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tinytorch_dir=project_root / 'tinytorch',
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bin_dir=project_root / 'bin'
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)
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def validate(self, venv_path: Union[Path, str]='.venv') -> List[str]:
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"""Validate the configuration and return any issues."""
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issues = []
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# Check Python version
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if sys.version_info < self.python_min_version:
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issues.append(f"Python {'.'.join(map(str, self.python_min_version))}+ required, "
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f"found {sys.version_info.major}.{sys.version_info.minor}")
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# Check virtual environment (more robust detection)
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in_venv = (
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# Method 1: Check VIRTUAL_ENV environment variable
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os.environ.get('VIRTUAL_ENV') is not None or
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# Method 2: Check sys.prefix vs sys.base_prefix
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(hasattr(sys, 'base_prefix') and sys.base_prefix != sys.prefix) or
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# Method 3: Check for sys.real_prefix (older Python versions)
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hasattr(sys, 'real_prefix') or
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# Method 4: Check if .venv directory exists and packages are available
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(venv_path.exists() and self._packages_available())
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)
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if not in_venv:
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issues.append(f"Virtual environment not activated. Run: source {venv_path}/bin/activate")
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# Check required directories
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if not self.assignments_dir.exists():
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issues.append(f"Assignments directory not found: {self.assignments_dir}")
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if not self.tinytorch_dir.exists():
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issues.append(f"TinyTorch package not found: {self.tinytorch_dir}")
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# Check required packages
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for package in self.required_packages:
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try:
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__import__(package)
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except ImportError:
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issues.append(f"Missing dependency: {package}. Run: pip install -r requirements.txt")
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return issues
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def _packages_available(self) -> bool:
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"""Check if required packages are available (helper for venv detection)."""
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try:
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for package in self.required_packages:
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__import__(package)
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return True
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except ImportError:
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return False |